OpenRaiser/Intern-Atlas huggingface dataset:
SPRESSO: A Secure, Privacy-Respecting Single Sign-On System for the Web
Venue: arXiv cs.CR 2015
Year: 2015

Single sign-on (SSO) systems, such as OpenID and OAuth, allow web sites, so-called relying parties (RPs), to delegate user authentication to identity providers (IdPs), such as Facebook or Google. These systems are very popular, as they provide a convenient means for users to log in at RPs and move much of the burden of user authentication from RPs to IdPs. There is, however, a downside to current systems, as they do not respect users' privacy: IdPs learn at which RP a user logs in. With one exception, namely Mozilla's BrowserID system (a.k.a. Mozilla Persona), current SSO systems were not even designed with user privacy in mind. Unfortunately, recently discovered attacks, which exploit design flaws of BrowserID, show that BrowserID does not provide user privacy either. In this paper, we therefore propose the first privacy-respecting SSO system for the web, called SPRESSO (for Secure Privacy-REspecting Single Sign-On). The system is easy to use, decentralized, and platform independent. It is based solely on standard HTML5 and web features and uses no browser extensions, plug-ins, or other executables. Existing SSO systems and the numerous attacks on such systems illustrate that the design of secure SSO systems is highly non-trivial. We therefore also carry out a formal analysis of SPRESSO based on an expressive model of the web in order to formally prove that SPRESSO enjoys strong authentication and privacy properties.
An Adaptive Transmission Protocol for Wireless-Powered Cooperative Communications
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we consider a wireless-powered cooperative communication network, which consists of one hybrid access point (AP), one source and one relay to assist information transmission. Unlike conventional cooperative networks, the source and relay are assumed to have no embedded energy supplies in the considered system. Hence, they need to first harvest energy from the radio-frequency (RF) signals radiated by the AP in the downlink (DL) before information transmission in the uplink (UL). Inspired by the recently proposed harvest-then-transmit (HTT) and harvest-then-cooperate (HTC) protocols, we develop a new adaptive transmission (AT) protocol. In the proposed protocol, at the beginning of each transmission block, the AP charges the source. AP and source then perform channel estimation to acquire the channel state information (CSI) between them. Based on the CSI estimate, the AP adaptively chooses the source to perform UL information transmission either directly or cooperatively with the relay. We derive an approximate closed-form expression for the average throughput of the proposed AT protocol over Nakagami-m fading channels. The analysis is then verified by Monte Carlo simulations. Results show that the proposed AT protocol considerably outperforms both the HTT and HTC protocols.
On Practical Aspects of Mobile Data Offloading to Wi-Fi Networks
Venue: arXiv cs.NI 2015
Year: 2015

Data traffic over cellular networks is exhibiting an ongoing exponential growth, increasing by an order of magnitude every year and has already surpassed voice traffic. This increase in data traffic demand has led to a need for solutions to enhance capacity provision, whereby traffic offloading to Wi-Fi is one means that can enhance realised capacity. Though offloading to Wi-Fi networks has matured over the years, a number of challenges are still being faced by operators to its realization. In this article, we carry out a survey of the practical challenges faced by operators in data traffic offloading to Wi-Fi networks. We also provide recommendations to successfully address these challenges.
Closed, Palindromic, Rich, Privileged, Trapezoidal, and Balanced Words in Automatic Sequences
Venue: arXiv cs.FL 2015
Year: 2015

We prove that the property of being closed (resp., palindromic, rich, privileged trapezoidal, balanced) is expressible in first-order logic for automatic (and some related) sequences. It therefore follows that the characteristic function of those n for which an automatic sequence x has a closed (resp., palindromic, privileged, rich, trape- zoidal, balanced) factor of length n is automatic. For privileged words this requires a new characterization of the privileged property. We compute the corresponding characteristic functions for various famous sequences, such as the Thue-Morse sequence, the Rudin-Shapiro sequence, the ordinary paperfolding sequence, the period-doubling sequence, and the Fibonacci sequence. Finally, we also show that the function counting the total number of palindromic factors in a prefix of length n of a k-automatic sequence is not k-synchronized.
10 Observations on Google Cluster Trace + 2 Measures for Cluster Utilization Enhancement
Venue: arXiv cs.DC 2015
Year: 2015

Utilization enhancement is a key concern to cluster owners. Google's cluster manager named Borg manages its clusters at an overall utilization higher than many others' clusters. Recently, Google has disclosed the details of its powerful cluster manager Borg. Quite a few lessons are summarized from the Borg experiences. Nevertheless, we find that more can be learned if the Borg design is correlated with the trace analysis of a Google cluster managed by Borg. There is one such trace released four years ago. In this paper, we analyze the Google cluster trace and make 10 observations not found in previous analyses. We also correlates the results of our analysis and previous analyses to the Borg design, such that we find two measures that can possibly further improve cluster utilization over Borg.
Feature-based Decipherment for Large Vocabulary Machine Translation
Venue: arXiv cs.CL 2015
Year: 2015

Orthographic similarities across languages provide a strong signal for probabilistic decipherment, especially for closely related language pairs. The existing decipherment models, however, are not well-suited for exploiting these orthographic similarities. We propose a log-linear model with latent variables that incorporates orthographic similarity features. Maximum likelihood training is computationally expensive for the proposed log-linear model. To address this challenge, we perform approximate inference via MCMC sampling and contrastive divergence. Our results show that the proposed log-linear model with contrastive divergence scales to large vocabularies and outperforms the existing generative decipherment models by exploiting the orthographic features.
A High-Level Modeling Language for the Efficient Design, Implementation, and Testing of Android Applications
Venue: arXiv cs.SE 2015
Year: 2015

Developing mobile applications remains difficult, time consuming, and error-prone, in spite of the number of existing platforms and tools. In this paper, we define MoDroid, a high-level modeling language to ease the development of Android applications. MoDroid allows developing models representing the core of applications. MoDroid provides Android programmers with the following advantages: (1) Models are built using high-level primitives that abstract away several implementation details; (2) It allows the definition of interfaces between models to automatically compose them; (3) Java native android can be automatically generated along with the required permissions; (4) It supports efficient model-based testing that operates on models. MoDroid is fully implemented and was used to develop several non-trivial Android applications.
On the Performance of Multiple Antenna Cooperative Spectrum Sharing Protocol under Nakagami-m Fading
Venue: arXiv cs.NI 2015
Year: 2015

In a cooperative spectrum sharing (CSS) protocol, two wireless systems operate over the same frequency band albeit with different priorities. The secondary (or cognitive) system which has a lower priority, helps the higher priority primary system to achieve its target rate by acting as a relay and allocating a fraction of its power to forward the primary signal. The secondary system in return is benefited by transmitting its own data on primary system's spectrum. In this paper, we have analyzed the performance of multiple antenna cooperative spectrum sharing protocol under Nakagami-m Fading. Closed form expressions for outage probability have been obtained by varying the parameters m and Omega of the Nakagami-m fading channels. Apart from above, we have shown the impact of power allocation factor (alpha) and parameter m on the region of secondary spectrum access, conventionally defined as critical radius for the secondary system. A comparison between theoretical and simulated results is also presented to corroborate the theoretical results obtained in this paper
Joint Robust Transmit/Receive Adaptive Beamforming for MIMO Radar Using Probability-Constrained Optimization
Venue: arXiv cs.IT 2015
Year: 2015

A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.
Measuring Word Significance using Distributed Representations of Words
Venue: arXiv cs.CL 2015
Year: 2015

Distributed representations of words as real-valued vectors in a relatively low-dimensional space aim at extracting syntactic and semantic features from large text corpora. A recently introduced neural network, named word2vec (Mikolov et al., 2013a; Mikolov et al., 2013b), was shown to encode semantic information in the direction of the word vectors. In this brief report, it is proposed to use the length of the vectors, together with the term frequency, as measure of word significance in a corpus. Experimental evidence using a domain-specific corpus of abstracts is presented to support this proposal. A useful visualization technique for text corpora emerges, where words are mapped onto a two-dimensional plane and automatically ranked by significance.
FactorBase: SQL for Learning A Multi-Relational Graphical Model
Venue: arXiv cs.DB 2015
Year: 2015

We describe FactorBase, a new SQL-based framework that leverages a relational database management system to support multi-relational model discovery. A multi-relational statistical model provides an integrated analysis of the heterogeneous and interdependent data resources in the database. We adopt the BayesStore design philosophy: statistical models are stored and managed as first-class citizens inside a database. Whereas previous systems like BayesStore support multi-relational inference, FactorBase supports multi-relational learning. A case study on six benchmark databases evaluates how our system supports a challenging machine learning application, namely learning a first-order Bayesian network model for an entire database. Model learning in this setting has to examine a large number of potential statistical associations across data tables. Our implementation shows how the SQL constructs in FactorBase facilitate the fast, modular, and reliable development of highly scalable model learning systems.
Unified Acceleration Method for Packing and Covering Problems via Diameter Reduction
Venue: arXiv cs.DS 2015
Year: 2015

The linear coupling method was introduced recently by Allen-Zhu and Orecchia for solving convex optimization problems with first order methods, and it provides a conceptually simple way to integrate a gradient descent step and mirror descent step in each iteration. The high-level approach of the linear coupling method is very flexible, and it has shown initial promise by providing improved algorithms for packing and covering linear programs. Somewhat surprisingly, however, while the dependence of the convergence rate on the error parameter $ε$ for packing problems was improved to $O(1/ε)$, which corresponds to what accelerated gradient methods are designed to achieve, the dependence for covering problems was only improved to $O(1/ε^{1.5})$, and even that required a different more complicated algorithm. Given the close connections between packing and covering problems and since previous algorithms for these very related problems have led to the same $ε$ dependence, this discrepancy is surprising, and it leaves open the question of the exact role that the linear coupling is playing in coordinating the complementary gradient and mirror descent step of the algorithm. In this paper, we clarify these issues for linear coupling algorithms for packing and covering linear programs, illustrating that the linear coupling method can lead to improved $O(1/ε)$ dependence for both packing and covering problems in a unified manner, i.e., with the same algorithm and almost identical analysis. Our main technical result is a novel diameter reduction method for covering problems that is of independent interest and that may be useful in applying the accelerated linear coupling method to other combinatorial problems.
Time Versus Cost Tradeoffs for Deterministic Rendezvous in Networks
Venue: arXiv cs.DC 2015
Year: 2015

Two mobile agents, starting from different nodes of a network at possibly different times, have to meet at the same node. This problem is known as $\mathit{rendezvous}$. Agents move in synchronous rounds. Each agent has a distinct integer label from the set $\{1,\dots,L\}$. Two main efficiency measures of rendezvous are its $\mathit{time}$ (the number of rounds until the meeting) and its $\mathit{cost}$ (the total number of edge traversals). We investigate tradeoffs between these two measures. A natural benchmark for both time and cost of rendezvous in a network is the number of edge traversals needed for visiting all nodes of the network, called the exploration time. Hence we express the time and cost of rendezvous as functions of an upper bound $E$ on the time of exploration (where $E$ and a corresponding exploration procedure are known to both agents) and of the size $L$ of the label space. We present two natural rendezvous algorithms. Algorithm $\mathtt{Cheap}$ has cost $O(E)$ (and, in fact, a version of this algorithm for the model where the agents start simultaneously has cost exactly $E$) and time $O(EL)$. Algorithm $\mathtt{Fast}$ has both time and cost $O(E\log L)$. Our main contributions are lower bounds showing that, perhaps surprisingly, these two algorithms capture the tradeoffs between time and cost of rendezvous almost tightly. We show that any deterministic rendezvous algorithm of cost asymptotically $E$ (i.e., of cost $E+o(E)$) must have time $Ω(EL)$. On the other hand, we show that any deterministic rendezvous algorithm with time complexity $O(E\log L)$ must have cost $Ω(E\log L)$.
Security Incident Response Criteria: A Practitioner's Perspective
Venue: arXiv cs.CR 2015
Year: 2015

Industrial reports indicate that security incidents continue to inflict large financial losses on organizations. Researchers and industrial analysts contend that there are fundamental problems with existing security incident response process solutions. This paper presents the Security Incident Response Criteria (SIRC) which can be applied to a variety of security incident response approaches. The criteria are derived from empirical data based on in-depth interviews conducted within a Global Fortune 500 organization and supporting literature. The research contribution of this paper is twofold. First, the criteria presented in this paper can be used to evaluate existing security incident response solutions and second, as a guide, to support future security incident response improvement initiatives.
Type-Constrained Representation Learning in Knowledge Graphs
Venue: arXiv cs.AI 2015
Year: 2015

Large knowledge graphs increasingly add value to various applications that require machines to recognize and understand queries and their semantics, as in search or question answering systems. Latent variable models have increasingly gained attention for the statistical modeling of knowledge graphs, showing promising results in tasks related to knowledge graph completion and cleaning. Besides storing facts about the world, schema-based knowledge graphs are backed by rich semantic descriptions of entities and relation-types that allow machines to understand the notion of things and their semantic relationships. In this work, we study how type-constraints can generally support the statistical modeling with latent variable models. More precisely, we integrated prior knowledge in form of type-constraints in various state of the art latent variable approaches. Our experimental results show that prior knowledge on relation-types significantly improves these models up to 77% in link-prediction tasks. The achieved improvements are especially prominent when a low model complexity is enforced, a crucial requirement when these models are applied to very large datasets. Unfortunately, type-constraints are neither always available nor always complete e.g., they can become fuzzy when entities lack proper typing. We show that in these cases, it can be beneficial to apply a local closed-world assumption that approximates the semantics of relation-types based on observations made in the data.
Space-Time Diagram Generation for Profiling Multi Agent Systems
Venue: arXiv cs.MA 2015
Year: 2015

Advances in Agent Oriented Software Engineering have focused on the provision of frameworks and toolkits to aid in the creation of Multi Agent Systems (MASs). However, despite the need to address the inherent complexity of such systems, little progress has been made in the development of tools to allow for the debugging and understanding of their inner workings. This paper introduces a novel performance analysis system, named AgentSpotter, which facilitates such analysis. AgentSpotter was developed by mapping conventional profiling concepts to the domain of MASs. We outline its integration into the Agent Factory multi agent framework.
In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap
Venue: arXiv cs.IT 2015
Year: 2015

In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization in cellular networks. However, the explicit impact of spatial interference, imposed by FD communications, on uplink and downlink transmissions has been overlooked in the literature. This paper presents an extensive study of the explicit effect of FD communications on the uplink and downlink performances. For the sake of rigorous analysis, we develop a tractable framework based on stochastic geometry toolset. The developed model accounts for uplink truncated channel inversion power control in FD cellular networks. The study shows that FD communications improve the downlink throughput at the expense of significant degradation in the uplink throughput. Therefore, we propose a novel fine-grained duplexing scheme, denoted as $α$-duplex scheme, which allows a partial overlap between uplink and downlink frequency bands. To this end, we show that the amount of the overlap can be optimized via adjusting $α$ to achieve a certain design objective.
Space-efficient detection of unusual words
Venue: arXiv cs.DS 2015
Year: 2015

Detecting all the strings that occur in a text more frequently or less frequently than expected according to an IID or a Markov model is a basic problem in string mining, yet current algorithms are based on data structures that are either space-inefficient or incur large slowdowns, and current implementations cannot scale to genomes or metagenomes in practice. In this paper we engineer an algorithm based on the suffix tree of a string to use just a small data structure built on the Burrows-Wheeler transform, and a stack of $O(σ^2\log^2 n)$ bits, where $n$ is the length of the string and $σ$ is the size of the alphabet. The size of the stack is $o(n)$ except for very large values of $σ$. We further improve the algorithm by removing its time dependency on $σ$, by reporting only a subset of the maximal repeats and of the minimal rare words of the string, and by detecting and scoring candidate under-represented strings that $\textit{do not occur}$ in the string. Our algorithms are practical and work directly on the BWT, thus they can be immediately applied to a number of existing datasets that are available in this form, returning this string mining problem to a manageable scale.
A massively parallel multi-level approach to a domain decomposition method for the optical flow estimation with varying illumination
Venue: arXiv cs.CV 2015
Year: 2015

We consider a variational method to solve the optical flow problem with varying illumination. We apply an adaptive control of the regularization parameter which allows us to preserve the edges and fine features of the computed flow. To reduce the complexity of the estimation for high resolution images and the time of computations, we implement a multi-level parallel approach based on the domain decomposition with the Schwarz overlapping method. The second level of parallelism uses the massively parallel solver MUMPS. We perform some numerical simulations to show the efficiency of our approach and to validate it on classical and real-world image sequences.
Few common failure cases in mobile robots
Venue: arXiv cs.RO 2015
Year: 2015

A mobile robot deployed for remote inspection, surveying or rescue missions can fail due to various possibilities and can be hardware or software related. These failure scenarios necessitate manual recovery (self-rescue) of the robot from the environment. It would bring unforeseen challenges to recover the mobile robot if the environment where it was deployed had hazardous or harmful conditions (e.g. ionizing radiations). While it is not fully possible to predict all the failures in the robot, failures can be reduced by employing certain design/usage considerations. Few example failure cases based on real experiences are presented in this short article along with generic suggestions on overcoming the illustrated failure situations.
OOASP: Connecting Object-oriented and Logic Programming
Venue: arXiv cs.AI 2015
Year: 2015

Most of contemporary software systems are implemented using an object-oriented approach. Modeling phases -- during which software engineers analyze requirements to the future system using some modeling language -- are an important part of the development process, since modeling errors are often hard to recognize and correct. In this paper we present a framework which allows the integration of Answer Set Programming into the object-oriented software development process. OOASP supports reasoning about object-oriented software models and their instantiations. Preliminary results of the OOASP application in CSL Studio, which is a Siemens internal modeling environment for product configurators, show that it can be used as a lightweight approach to verify, create and transform instantiations of object models at runtime and to support the software development process during design and testing.
A New Weighted Information Generating Function for Discrete Probability Distributions
Venue: arXiv cs.IT 2015
Year: 2015

The object of this paper is to introduce a new weighted information generating function whose derivative at point 1 gives some well known measures of information. Some properties and particular cases of the proposed generating function have also been studied.